Modern electronic devices such as cellular telephones, smart phones, tablets, and so on are increasingly capable of customizing their behavior to accommodate particular environments or situations. For example, a device that is being used while in a moving vehicle may behave differently than a device that is being used in a stationary location. However, such devices seldom have direct knowledge of their usage environment, and as such, the environment may need to be inferred or predicted based on other factors.
While current prediction models may allow some predictions to be made, such models are generally insufficient. For example, while it may be possible to efficiently encode models to solve linear problems, e.g., via linear regression, there is no suitable general solution to efficiently encode models to be used at the prediction phase in both linear and nonlinear systems.
The present disclosure is directed to a system that may exhibit numerous distinctions or advantages over prior systems. However, it should be appreciated that any particular distinction or advantage is not a limitation on the scope of the disclosed principles nor of the attached claims, except to the extent expressly noted. Additionally, the discussion of any problem in this Background section is not an indication that the problem represents known prior art.